Extensible TensorFlow Implementations of Projection Quality Metrics

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dc.contributor.authorMachado, Alisteren_US
dc.contributor.authorBehrisch, Michaelen_US
dc.contributor.authorTelea, Alexandruen_US
dc.contributor.editorGillmann, Christinaen_US
dc.contributor.editorKrone, Michaelen_US
dc.contributor.editorReina, Guidoen_US
dc.contributor.editorWischgoll, Thomasen_US
dc.date.accessioned2025-05-26T07:19:02Z
dc.date.available2025-05-26T07:19:02Z
dc.date.issued2025
dc.description.abstractDimensionality Reduction (DR, also called Projection) algorithms enable the exploration of high-dimensional data by generating low-dimensional representations of it - typically 2D or 3D scatterplots. Such representations are designed to map data patterns to visual patterns analyzable by humans. Projections can vary wildly - even for a fixed dataset - depending on technique and hyperparameters chosen and, as such, do not all preserve all data patterns equally well. To assess this, so-called Projection Quality Metrics (PQMs) are used. However, the ever-growing number of Projection Quality Metrics has led to fragmented implementations which hinder their easy reuse, leading in turn to unequal adoption and inconsistent implementations. In this work, we propose a TensorFlow-based library of PQMs, improving the previous state of the art in terms of ergonomics, extensibility, and computational scalability. We discuss our improvements and elicit areas where the gap between implementation and research is significant in the area of Projection Quality Metrics, pointing to avenues for future work in developing better PQM libraries that aim to fill this gap.en_US
dc.description.sectionheadersPaper Session 2
dc.description.seriesinformationVisGap - The Gap between Visualization Research and Visualization Software
dc.identifier.doi10.2312/visgap.20251160
dc.identifier.isbn978-3-03868-289-9
dc.identifier.pages8 pages
dc.identifier.urihttps://doi.org/10.2312/visgap.20251160
dc.identifier.urihttps://diglib.eg.org/handle/10.2312/visgap20251160
dc.publisherThe Eurographics Associationen_US
dc.rightsAttribution 4.0 International License
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectCCS Concepts: Software and its engineering → Software libraries and repositories; Mathematics of computing → Dimensionality reduction; General and reference → Metrics
dc.subjectSoftware and its engineering → Software libraries and repositories
dc.subjectMathematics of computing → Dimensionality reduction
dc.subjectGeneral and reference → Metrics
dc.titleExtensible TensorFlow Implementations of Projection Quality Metricsen_US
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